1 Introduction

In this notebook we will plot the scrublet doublet scores on the UMAPs computed in the previous notebook.

2 Pre-processing

2.1 Load packages

library(Seurat)
library(Signac)
library(tidyverse)

2.2 Parameters

# Paths
path_to_obj <- here::here("multiome/results/R_objects/5.tonsil_multiome_integrated_using_wnn.rds")


# Thresholds
max_doublet_score_rna <- 0.3
max_doublet_score_atac <- 0.3

2.3 Load data

tonsil <- readRDS(path_to_obj)

3 Doublet score

3.1 Scrublet doublet score (ATAC)

hist_atac <- tonsil@meta.data %>%
  ggplot(aes(scrublet_doublet_scores_atac)) +
    geom_histogram(bins = 30) +
    geom_vline(
      xintercept = max_doublet_score_atac,
      linetype = "dashed",
      color = "red"
    ) +
    xlab("Doublet Score (ATAC)") +
    theme_bw() +
    theme(
      axis.title = element_text(size = 13),
      axis.text = element_text(size = 11)
    )
hist_atac

3.2 Scrublet doublet score (RNA)

hist_rna <- tonsil@meta.data %>%
  ggplot(aes(scrublet_doublet_scores)) +
    geom_histogram(bins = 30) +
    geom_vline(
      xintercept = max_doublet_score_rna,
      linetype = "dashed",
      color = "red"
    ) +
    xlab("Doublet Score (RNA)") +
    theme_bw() +
    theme(
      axis.title = element_text(size = 13),
      axis.text = element_text(size = 11)
    )
hist_rna

3.3 Correlation

scatter_plot <- tonsil@meta.data %>%
  ggplot(aes(scrublet_doublet_scores, scrublet_doublet_scores_atac)) +
    geom_point(size = 0.01, alpha = 0.75) +
    geom_vline(xintercept = max_doublet_score_rna, linetype = "dashed", color = "red") +
    geom_hline(yintercept = max_doublet_score_atac, linetype = "dashed", color = "red") +
    labs(x = "Doublet Score (RNA)", y = "Doublet Score (ATAC)") +
    theme_bw() +
    theme(
      axis.title = element_text(size = 13),
      axis.text = element_text(size = 11)
    )
scatter_plot

3.4 Projection

3.4.1 ATAC-driven UMAP

# Define doublets
doublets_comparison <- 
  tonsil$scrublet_doublet_scores > max_doublet_score_rna |
  tonsil$scrublet_doublet_scores_atac > max_doublet_score_atac
tonsil$is_doublet <- doublets_comparison


# Plot
feat_plot1 <- FeaturePlot(
  tonsil,
  features = "scrublet_doublet_scores",
  reduction = "umap.atac",
  pt.size = 0.1
)
feat_plot2 <- FeaturePlot(
  tonsil,
  features = "scrublet_doublet_scores_atac",
  reduction = "umap.atac",
  pt.size = 0.1
)
dim_plot1 <- DimPlot(
  tonsil,
  group.by = "is_doublet",
  reduction = "umap.atac",
  pt.size = 0.1
)
feat_plot1

feat_plot2

dim_plot1

3.4.2 RNA-driven UMAP

feat_plot3 <- FeaturePlot(
  tonsil,
  features = "scrublet_doublet_scores",
  reduction = "umap.rna",
  pt.size = 0.1
)
feat_plot4 <- FeaturePlot(
  tonsil,
  features = "scrublet_doublet_scores_atac",
  reduction = "umap.rna",
  pt.size = 0.1
)
dim_plot2 <- DimPlot(
  tonsil,
  group.by = "is_doublet",
  reduction = "umap.rna",
  pt.size = 0.1
)
feat_plot3

feat_plot4

dim_plot2

Canonical markers:

canonical_markers <- c("CD3D", "CD79B", "NKG7", "LYZ", "FDCSP")
canonical_markers_gg <- purrr::map(canonical_markers, function(x) {
  p <- FeaturePlot(
    tonsil,
    features = x,
    reduction = "umap.rna",
    pt.size = 0.1
  )
  p
})
canonical_markers_gg
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As we can see, there are clearly two clusters of cells that are B-T cell clusters. In the next notebook we will overcluster to discard those.

4 Session Information

sessionInfo()
## R version 4.0.3 (2020-10-10)
## Platform: x86_64-apple-darwin13.4.0 (64-bit)
## Running under: macOS Big Sur 10.16
## 
## Matrix products: default
## BLAS/LAPACK: /Users/pauli/opt/anaconda3/envs/Tonsil_atlas/lib/libopenblasp-r0.3.10.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
##  [1] forcats_0.5.0     stringr_1.4.0     dplyr_1.0.2       purrr_0.3.4       readr_1.4.0       tidyr_1.1.2       tibble_3.0.4      ggplot2_3.3.2     tidyverse_1.3.0   Signac_1.1.0.9000 Seurat_3.9.9.9010 BiocStyle_2.16.1 
## 
## loaded via a namespace (and not attached):
##   [1] reticulate_1.18             tidyselect_1.1.0            RSQLite_2.2.1               AnnotationDbi_1.50.3        htmlwidgets_1.5.2           grid_4.0.3                  BiocParallel_1.22.0         Rtsne_0.15                  munsell_0.5.0               codetools_0.2-17            ica_1.0-2                   future_1.20.1               miniUI_0.1.1.1              withr_2.3.0                 colorspace_2.0-0            Biobase_2.48.0              OrganismDbi_1.30.0          knitr_1.30                  rstudioapi_0.12             stats4_4.0.3                ROCR_1.0-11                 tensor_1.5                  listenv_0.8.0               labeling_0.4.2              GenomeInfoDbData_1.2.3      polyclip_1.10-0             farver_2.0.3                bit64_4.0.5                 rprojroot_2.0.2             parallelly_1.21.0           vctrs_0.3.4                 generics_0.1.0              xfun_0.18                   biovizBase_1.36.0           BiocFileCache_1.12.1        lsa_0.73.2                  ggseqlogo_0.1               R6_2.5.0                    GenomeInfoDb_1.24.0         rsvd_1.0.3                  AnnotationFilter_1.12.0     bitops_1.0-6               
##  [43] spatstat.utils_1.17-0       reshape_0.8.8               DelayedArray_0.14.0         assertthat_0.2.1            promises_1.1.1              scales_1.1.1                nnet_7.3-14                 gtable_0.3.0                globals_0.13.1              goftest_1.2-2               ggbio_1.36.0                ensembldb_2.12.1            rlang_0.4.8                 RcppRoll_0.3.0              splines_4.0.3               rtracklayer_1.48.0          lazyeval_0.2.2              dichromat_2.0-0             broom_0.7.2                 checkmate_2.0.0             modelr_0.1.8                BiocManager_1.30.10         yaml_2.2.1                  reshape2_1.4.4              abind_1.4-5                 GenomicFeatures_1.40.1      backports_1.2.0             httpuv_1.5.4                Hmisc_4.4-1                 RBGL_1.64.0                 tools_4.0.3                 bookdown_0.21               ellipsis_0.3.1              RColorBrewer_1.1-2          BiocGenerics_0.34.0         ggridges_0.5.2              Rcpp_1.0.5                  plyr_1.8.6                  base64enc_0.1-3             progress_1.2.2              zlibbioc_1.34.0             RCurl_1.98-1.2             
##  [85] prettyunits_1.1.1           rpart_4.1-15                openssl_1.4.3               deldir_0.2-3                pbapply_1.4-3               cowplot_1.1.0               S4Vectors_0.26.0            zoo_1.8-8                   haven_2.3.1                 SummarizedExperiment_1.18.1 ggrepel_0.8.2               cluster_2.1.0               here_1.0.1                  fs_1.5.0                    magrittr_1.5                data.table_1.13.2           reprex_0.3.0                lmtest_0.9-38               RANN_2.6.1                  SnowballC_0.7.0             ProtGenerics_1.20.0         fitdistrplus_1.1-1          matrixStats_0.57.0          hms_0.5.3                   patchwork_1.1.0             mime_0.9                    evaluate_0.14               xtable_1.8-4                XML_3.99-0.3                jpeg_0.1-8.1                readxl_1.3.1                IRanges_2.22.1              gridExtra_2.3               compiler_4.0.3              biomaRt_2.44.4              KernSmooth_2.23-17          crayon_1.3.4                htmltools_0.5.0             mgcv_1.8-33                 later_1.1.0.1               Formula_1.2-4               lubridate_1.7.9            
## [127] DBI_1.1.0                   tweenr_1.0.1                dbplyr_1.4.4                MASS_7.3-53                 rappdirs_0.3.1              Matrix_1.2-18               cli_2.1.0                   parallel_4.0.3              igraph_1.2.6                GenomicRanges_1.40.0        pkgconfig_2.0.3             GenomicAlignments_1.24.0    foreign_0.8-80              plotly_4.9.2.1              xml2_1.3.2                  XVector_0.28.0              rvest_0.3.6                 VariantAnnotation_1.34.0    digest_0.6.27               sctransform_0.3.1           RcppAnnoy_0.0.16            graph_1.66.0                spatstat.data_1.4-3         Biostrings_2.56.0           cellranger_1.1.0            rmarkdown_2.5               leiden_0.3.5                fastmatch_1.1-0             htmlTable_2.1.0             uwot_0.1.8.9001             curl_4.3                    shiny_1.5.0                 Rsamtools_2.4.0             lifecycle_0.2.0             nlme_3.1-150                jsonlite_1.7.1              fansi_0.4.1                 viridisLite_0.3.0           askpass_1.1                 BSgenome_1.56.0             pillar_1.4.6                lattice_0.20-41            
## [169] GGally_2.0.0                fastmap_1.0.1               httr_1.4.2                  survival_3.2-7              glue_1.4.2                  spatstat_1.64-1             png_0.1-7                   bit_4.0.4                   ggforce_0.3.2               stringi_1.5.3               blob_1.2.1                  latticeExtra_0.6-29         memoise_1.1.0               irlba_2.3.3                 future.apply_1.6.0